Music recommendation method with respect to message service

ABSTRACT

A music recommendation method and a music recommendation system are provided. The music recommendation method includes: selecting music files according to a theme of the message service and music, a mood of the music, a similarity between content of the message service and content of the music; and recommending selected music files to a user.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. Ser. No. 11/889,622, filedAug. 15, 2007, the disclosure of which is incorporated herein in itsentirety by reference. This application claims the benefit of KoreanPatent Application No. 10-2006-0127171, filed on Dec. 13, 2006, in theKorean Intellectual Property Office, the disclosure of which isincorporated herein by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a music recommendation method which canautomatically recommend appropriate music when transmitting a messageservice in a personal communication terminal, and a system using themethod. More particularly, the present invention relates to a musicrecommendation method which can select a music file according to a themeof the music, a mood of the music, and a similarity between content of amessage service and content of the music, and automatically recommend auser the selected music file.

2. Description of Related Art

Currently, since a personal communication terminal such as a mobilephone tends to provide various multimedia functions, there is a tendencyin a message service to also provide a multimedia messaging service(MMS) that may attach to transmit a photo, music, and a moving pictureincluded in the message service. An amount of use of the MMS will berapidly spread since it is possible to transmit a long e-mail ormultimedia contents in the personal communication terminal. However,various functions which enable a user to easily use the MMS are neededsince the user has an aversion to use the MMS due to inconveniences ofprocedures for transmitting the MMS and a user interface.

Currently, the personal communication terminal can transmit the musicfile while transmitting a message of a message service via the MMS, andcan store various types of music files in a memory where the music filesare stored according to a capacity of the memory is increase. However, aconventional communication terminal has a problem in that, it takes agreat amount of time and a great amount of effort to search for anappropriate music file for the message service among stored music filesvia the MMS. Accordingly, when the user uses the MMS via the personalcommunication terminal, a new method capable of easily searching for amusic file for attachment is needed.

In the conventional art, as an example of selecting appropriate musicfor an e-mail, there is a method which can automatically select musicbased on an impression of the music. In the conventional method,character strings are detected from the e-mail, the detected characterstrings are converted into an impression value using a conversion table,an impression value database of the music is compared with theimpression value, and consequently the appropriate music is selected. Inthis instance, the impression value indicates a reference value whichshows emotions felt by a user when the user feels the music. Theimpression value is analyzed from a physical feature of a music signal,and there are impression values such as extreme, liveliness, refresh,simplicity, tenderness. However, in the conventional art, there is aproblem in that, the appropriate music is not accurately selected sincethe method exclusively relies on the impressions of the music, i.e. theappropriate music with respect to the e-mail is selected by exclusivelyusing the impressions of the music, accordingly there is a probabilitythat a selected music does not corresponds to the e-mail.

Also, a personal communication terminal using the conventional art has aproblem in that, a user is required to navigate a plurality of selectedmusic on a limited small screen, and select appropriate music afterchecking the navigated music when a great number of music having anidentical impression value exist.

Also, the personal communication terminal using the convention art has aproblem in that, a recommendation rank of a plurality of selected musicmay not be rated since music having an impression value, correspondingto an e-mail, is randomly displayed.

BRIEF SUMMARY

An aspect of the present invention provides a music recommendationmethod which can select a music file according to a theme of the music,a mood of the music, and a similarity between content of a messageservice and content of the music, and automatically recommend to a userthe selected music file, and a music recommendation system using themethod.

An aspect of the present invention also provides a music recommendationmethod which can classify a title of music, lyrics of the music, and atext of a message service according to a theme, compare the classifiedtheme, and select the music as a result of the comparison, and a musicrecommendation system using the method.

An aspect of the present invention also provides a music recommendationmethod which can recommend music, which is matched with a theme of amessage service, by classifying music according to a theme, and alsoclassifying the music according to a mood in a personal communicationterminal, and a music recommendation system using the method.

An aspect of the present invention also provides a music recommendationmethod which can accurately select music, which is matched with amessage service, by calculating a similarity between content of lyricsand content of the message service, and a music recommendation systemusing the method.

According to an aspect of the present invention, there is provided amusic recommendation method in a personal communication terminal,including: selecting music files according to a theme of the messageservice and music, a mood of the music, a similarity between content ofthe message service and content of the music; and recommending selectedmusic files to a user.

According to another aspect of the present invention, there is provideda music recommendation system including: a music file selection unitselecting music files according to a theme of the message service andmusic, a mood of the music, a similarity between content of the messageservice, and content of the music; and a recommendation unitrecommending selected music files to a user.

Additional and/or other aspects and advantages of the present inventionwill be set forth in part in the description which follows and, in part,will be obvious from the description, or may be learned by practice ofthe invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and/or other aspects and advantages of the present inventionwill become apparent and more readily appreciated from the followingdetailed description, taken in conjunction with the accompanyingdrawings of which:

FIG. 1 is a diagram illustrating a music recommendation system withrespect to a message service according to an embodiment of the presentinvention;

FIG. 2 is a diagram illustrating an example of a configuration of amusic file selection unit of FIG. 1;

FIG. 3 is a diagram illustrating an example of a configuration of aselection unit of FIG. 2;

FIG. 4 is a diagram illustrating an example of a configuration of asecond filtering unit of FIG. 2;

FIG. 5 is a diagram illustrating an example of a configuration of atheme based music selection unit of FIG. 3;

FIG. 6 is a diagram illustrating an example of a configuration of alyrics theme classification unit, a title theme classification unit, anda message theme classification unit of FIG. 5;

FIG. 7 is a diagram illustrating an example of a theme matching tableand a mood matching table according to an exemplary embodiment of thepresent invention;

FIG. 8 is a flowchart illustrating a music recommendation method withrespect to a message service according to another embodiment of thepresent invention;

FIG. 9 is a flowchart illustrating an example of operations of analyzingthemes of FIG. 8;

FIG. 10 is a flowchart illustrating operations of classification ofmusic files according to a theme of FIG. 9;

FIG. 11 is a flowchart illustrating an example of operations ofselecting music files according to the theme of FIG. 9;

FIG. 12 is a flowchart illustrating an example of filtering of aplurality of music files according to a similarity of FIG. 9; and

FIG. 13 is a flowchart illustrating an example of operations ofclassification of a theme of lyrics, a theme of a title, and a theme ofa message service of FIG. 11.

DETAILED DESCRIPTION OF EMBODIMENTS

Reference will now be made in detail to exemplary embodiments of thepresent invention, examples of which are illustrated in the accompanyingdrawings, wherein like reference numerals refer to the like elementsthroughout. The exemplary embodiments are described below in order toexplain the present invention by referring to the figures.

FIG. 1 is a diagram illustrating a music recommendation system 100 withrespect to a message service according to an embodiment of the presentinvention.

Referring to FIG. 1, the music recommendation system 100 includes amusic file selection unit 110, a recommendation unit 120, and a musicfile collection 130.

A user inputs, via an input device of the music recommendation system100, a message service to transmit. Accordingly, the musicrecommendation system 100 may receive the message service via variousinput devices such as a keyboard, a keypad, and a touchpad, and thelike, (not shown) from the user.

Also, when the user wants to transmit the message service by attaching amusic file, the user selects whether to use the music file collection130 stored in a user terminal, or to use a music file which isdownloadable via a music download service on an Internet connection, asthe music file to be attached to the message service. Accordingly, themusic recommendation system 100 may receive a selection from the userwhether to use the music file collection 130 or to use the downloadablemusic file.

The music file selection unit 110 selects a music file according to atheme of the message service, a theme of the music, a mood of the music,and a similarity between content of the message service and content ofthe message service. Specifically, the music file selection unit 110classifies the message service and the music file according to the themeof the message service, the theme of the music, the mood of the music,and the similarity between content of the message service and content ofthe message service, and selects a music file according to a result ofthe classification. Hereinafter, a configuration and operations of themusic file selection unit 110 will be described in detail by referringto FIG. 2.

Referring to FIGS. 1 and 2, the music file selection unit 110 includes aselection unit 210, a first filtering unit 220, and a second filteringunit 230.

The selection unit 210 selects target music files, classifies the targetmusic files and a message service according to a theme, and selects,from among the target music, a music file which corresponds to the themeof the message service according to a result of the classification.Hereinafter, a configuration and operations of the selection unit 210will be described in detail by referring to FIG. 3.

Referring to FIGS. 1 through 3, the selection unit 210 includes a targetmusic selection unit 310 and a theme based music selection unit 320which selects music according to a theme.

The target music selection unit 310 selects either a music filecollection stored in a user terminal, or a music file which isdownloadable via a music download service on an Internet connection, asthe target music files. Specifically, the target music selection unit310 may select either the music file from among music files in the userterminal, or the music file which is downloadable using the musicdownload service on an Internet connection, as the target music files.The music recommendation system 100 receives a selection for the musicfile as the target music file, from the user via the target musicselection unit 310.

The theme based music selection unit 320, selecting the music accordingto the theme, classifies the target music files according to the theme,and selects a plurality of music files according to the classified themefrom among the target music files. Specifically, the theme based musicselection unit 320 selects, from among the target music files, theplurality of music files according to the classified themes of thetarget music files and message service. As described, the musicrecommendation system 100 of FIG. 1 analyzes the theme of the targetmusic files and the theme of the message service via the theme basedmusic selection unit 320, and selects, from among the target musicfiles, the plurality of the music files appropriate for the analyzedthemes of the message service. Hereinafter, a configuration andoperations of the theme based music selection unit 320 will be describedin detail by referring to FIG. 5.

FIG. 5 is a diagram illustrating an example of a configuration of thetheme based music selection unit 320 of FIG. 3.

Referring to FIG. 5, the theme based music selection unit 320 of FIG. 3includes a lyrics theme classification unit 510, a title themeclassification unit 520, a classification result merging unit 530, amessage theme classification unit 540, and a music selection unit 550.

The lyrics theme classification unit 510 classifies lyrics of musicfiles according to a theme. The lyrics theme classification unit 510 mayomit operation of theme classification with respect to the music fileswhen there is no information of the lyrics from the music files. Thetitle theme classification unit 520 classifies titles of music files.Specifically, the title theme classification unit 520 extracts the titleof a music file from an identification3 (ID3) tag of the music files ormusic file names of the music files, and classifies the title of themusic files using the extracted title of the music files.

The classification results merging unit 530 merges a result of theclassifications of the lyrics with a result of the title of music files,and outputs a theme of the music files.

The message theme classification unit 540 classifies a message serviceaccording to a theme, and outputs the classified theme of the messageservice.

The themes of the music files and the message service may be variouslydefined depending on categories such as sorrow, happiness, love, abreakup, yearning, spring, summer, autumn, winter, and a journey. When aspecific music does not fall into the defined categories, the specificmusic may be classified into the others.

The music selection unit 550 selects a music file based on a the musicfiles classified according to theme and the message service classifiedaccording to the theme. Specifically, the music selection unit 550 mayselect the music file which corresponds to the classified theme of themessage service.

FIG. 6 is a diagram illustrating an example of a configuration of thelyrics theme classification unit 510, the title theme classificationunit 520, and the message theme classification unit 540 of FIG. 5.

Referring to FIG. 6, the lyrics theme classification unit 510, the titletheme classification unit 520, and the message theme classification unit540 includes a theme classification learning unit 610 and a themeclassification unit 620.

The theme classification learning unit 520 performs learning for themeclassification of music files stored in the database 330 of FIG. 3 and amessage service, and includes a feature selection unit 611 and acategory index unit 612. The database 330 may be previously built forthe theme classification learning, and themes corresponding to the titleof music, lyrics of the music and a message service are classified inthe database 330. The music recommendation system 100 of FIG. 1 may usea lyrics database when it is difficult to build a database with respectto the message.

The feature selection unit 611 extracts feature candidates from thetitle of the music, the lyrics of the music stored in the database 330,the message service, and selects one feature to be used for the themeclassification using the extracted feature candidates. The featurecandidates may include a morpheme n-gram, a word n-gram, and a syllablen-gram. When a processing capability of the feature selection unit 611is sufficient, the feature selection unit 611 uses the morpheme n-gramas the feature candidates, and when the processing capability of thefeature selection unit 611 is insufficient for using the morphemen-gram, the feature selection unit 611 may use the word n-gram or thesyllable n-gram. The feature selection unit 611 may select the featurefrom the feature candidates using a mutual information scale, aninformation acquisition quantity, and Chi-square statistic. In themessage service, an emoticon has important information, and is used forthe feature since the emoticon is used for expressing emotions of auser. Accordingly, the emoticon is additionally collected to be used forthe feature.

The category index unit 612 indexes a category of each theme using theselected feature. Namely, the category index unit 612 may express thecategory of each theme as a category vector including features andvalues. Each theme category vector has all of the selected features asthe feature, and a feature of the category vector for each theme has ‘1’as a feature value when a corresponding feature is selected, the featureof the category vector for each theme has ‘0’ as the feature value whenthe corresponding feature is not selected. The category index unit 612outputs a result of the category index as the category vector.

The theme classification unit 620 classifies the theme of music filesstored in the user terminal, or provided from a web server, and thetheme of the message service inputted by the user, and includes apre-processing unit 621, an index unit 622, and a category allocationunit 623.

The pre-processing unit 621 performs pre-processing on the music filesand the message service in order to classify the music and the messageservice according to the theme. Namely, the pre-processing unit 621extracts a title and lyrics from the music files, and acquires textinformation or emoticon information from the music files and the messageservice. The title may be extracted from an ID3 tag of the music filesor the music file name.

The index unit 622 expresses the title, the lyrics of the music files,or the message service as a vector to index the expressed vector.Namely, the index unit 622 determines whether each feature of theselected feature is included in the title, the lyrics of the musicfiles, or the message service, and indexes a value according to a resultof the determination. Since words, directly associated with the theme ofthe music, are compressively shown in the title, the index unit 622 mayallocate to index ‘1’ when the feature is shown in the title, and mayallocate to index ‘0’ when the feature is not shown in the title afterapplying a binary weight to each of the feature values. The index unit622 may allocate to index a frequency number, i.e. how many times acorresponding word occurs in the text, to the feature value by applyinga frequency weight to the lyrics and the message service. The index unit622 may output a result of the index as a vector.

The category allocation unit 623 determines the theme of the title, thelyric, and the message service using the category vector, the musicvector, or the message vector, and allocates each category whichcorresponds to the determined theme. Specifically, the categoryallocation unit 623 determines the theme by measuring a similaritybetween the theme category vector, obtained by the category index unit612, and the title, the lyrics, and the message service vectors, andallocates the each category which corresponds to the determined theme.As an example, a vector dot product (abcosθ) or a cosine similarity maybe used for the vector similarity.

The first filtering unit 220 of FIG. 2 analyzes the plurality of musicfiles according to a mood, and filters out the plurality of music files,selected by the selection unit 210 of FIG. 2, based on the analyzedmood. Specifically, the first filtering unit 220 deletes music fileswhose theme of the music files and mood of the music files are notmatched with each other. A matching relation between the mood of themusic files and the theme of the music files may be understood byreferring to a matching table in FIG. 7.

FIG. 7 is a diagram illustrating an example of a theme matching tableand a mood matching table according to an exemplary embodiment of thepresent invention.

Referring to FIG. 7, a theme of a message service and a mood of a musicfile are matched with each other in the matching table. The theme of themessage service includes happiness, sorrow, a journey, a yearning, etc.,the mood of the music file includes pleasant, sad, calm, exciting, etc.,and various types of classification may be used. The matching table maybe stored in the database 330 of FIG. 3. There is a probability that atheme of music and a mood of the music do not match each other, fromamong the music files which correspond to the theme of the messageservice. As an example, when the theme of the music is a ‘breakup’, andthe mood of the music is ‘pleasant’, this indicates the theme of themusic and the mood of the music are not matched with each other.

Accordingly, the music recommendation system 100 of FIG. 1 deletes themusic file whose mood of music does not match a theme of music. As anexample, when a theme of the message service is ‘breakup’ whileselecting the music, the music recommendation system 100 deletes a musicfile having an inappropriate mood for the theme of the music using themood of the music, from among the selected music files, in order toprevent selecting a music file whose mood is pleasant, and selects amusic file having an appropriate mood for the theme of the music. Inthis case, the music recommendation system 100 uses the mapping table inorder to filter out the selected music file.

As an example, when a theme of the music file or a theme of the messageservice is ‘happiness’, and a mood of music corresponding to the themeis ‘pleasant’, a first filtering unit 220 of FIG. 2 may select musicfiles whose mood of the music is ‘pleasant’ by filtering out music filesfrom a plurality of music files whose mood of the music is not‘pleasant’.

As an another example, when a theme of the music file or a theme of themessage service is ‘sorrow’, a mood of music corresponding to the themeis ‘sorrow’ or ‘calm’, a first filtering unit 220 may select music fileswhose mood of the music is ‘sorrow’ by filtering out music files whosemood of the music is not ‘sorrow’ or ‘calm’ from the plurality of musicfiles.

As still another example, when a theme of the music file or a theme ofthe message service is ‘journey’, a mood of music corresponding to thetheme is ‘exciting’, a first filtering unit 220 may select music fileswhose mood of the music is ‘exciting’ by filtering out music files whosemood of the music is not ‘exciting’ of the plurality from music files.

As yet another example, when a theme of the music file or a theme of themessage service is ‘yearning’, a mood of music corresponding to thetheme is ‘calm’, a first filtering unit 220 may select music files whosemood of the music is ‘calm’ by filtering out music files whose mood ofthe music is not ‘calm’ from the plurality of music files.

As described above, the music recommendation system 100 may provide auser with an appropriate number of music files when the appropriatenumber of music files is selected by the first filtering unit 220.However, when a number of a selected music files is great, there is aprobability that there are music having an identical theme or mood, orthe user wants to show something different via a message service even ifmusic has an identical theme. Accordingly, the music recommendationsystem 100 according to the present invention measures a similaritybetween content of lyrics of music and content of a message service viaa second filtering unit 230 of FIG. 2, and filters out the musicaccording to the similarity.

The second filtering unit 230 calculates the similarity between thecontent of the message and the content of the music file, and filtersout the music files according to the similarity.

The second filtering unit 230 may be omitted in order to increase aspeed of the music recommendation system 100, or the second filteringunit 230 may be omitted when the number of music files selected by thefirst filtering unit 220 is relatively few. Hereinafter, a configurationand operations of the second filtering unit 230 will be described indetail by referring to FIG. 4.

FIG. 4 is a diagram illustrating an example of a configuration of asecond filtering unit 230 of FIG. 2.

Referring to FIG. 4, the second filtering unit 230 includes a messageindex unit 410, a lyrics index unit 420, a similarity calculation unit430, a comparison unit 440, and a selection unit 450.

The message index unit 410 indexes a message service inputted by a user.Specifically, the message index unit 410 extracts character strings of atext from the message service inputted by the user, and indexes themessage service by expressing the character strings of the text as avector. A morpheme n-gram and a word n-gram may be used for thecharacter strings of the text. The message index unit 410 may reduce anumber of features by selecting the morpheme n-gram or the word n-gram,including morphemes having a substantial meaning such as a noun and aninflected word. The feature, having been used in the index unit 622, maybe used for the feature of the vector.

The lyrics index unit 420 indexes the music files by expressing thelyrics and the title of the music files as a vector. In this case,features, which are indexed by the message index unit 410, may be used afeature for the vector. A feature value of the vector of the messageservice and features of the vectors of the lyrics and the title may beindexed by calculating a number of features occurring in the messageservice or the lyrics using a frequency weight.

The similarity calculation unit 430 calculates a similarity betweencontent of the music files and content of the message service.Specifically, the similarity calculation unit 430 calculates thesimilarity between the content of the music files and the content of themessage service using a vector of the indexed music files and a vectorof the indexed message service. A cosine similarity may be used for thesimilarity between the content of the music files and the content of themessage service.

The comparison unit 440 compares the similarity with a threshold value.The threshold value is defined via a predetermined experiment.Specifically, the comparison unit 440 compares the similarity with thethreshold value to determine whether the similarity between the contentof the music files and the content of the message service is greaterthan or equal to the threshold value, or less than the threshold value.When the similarity is less than the threshold value, operation processreturns to the message index unit 410.

The selection unit 450 selects, from among the indexed music files, themusic files when a similarity of a specific music file is greater thanthe threshold value. Specifically, the selection unit 450 may selectmusic files whose similarity between content of music files and contentof message service is greater than or equal to the threshold value.

The recommendation unit 120 of FIG. 1 recommends a music filecorresponding to the theme of the message service, based on a result ofthe analysis. Specifically, the recommendation unit 120 may recommendthe user a music list whose selected music files are arranged in adescending order according to a similarity. The recommendation unit 120may include a music arrangement unit and a music list providing unit.

The music arrangement unit arranges the selected music files based onthe similarity. The music arrangement unit may arrange the selectedmusic files using a category, having been calculated by the categoryallocation unit 623 of FIG. 6, and the similarity between music themes.Specifically, the music arrangement unit may arrange the selected musicfiles in an order similarity between the music themes and a themecategory vector corresponding to the theme of the message service. Also,the music arrangement unit may arrange the selected music files based onthe content similarity, having been calculated by the similaritycalculation unit 430 of the second filtering unit 230. Specifically, themusic arrangement unit may select music files in an order similaritywith respect to the theme and the content of the indexed music files andthe message service. The music arrangement unit may not operate when anumber of the indexed music files is insufficient to arrange the musicfiles, or the music arrangement unit may not operate by considering aspeed of selecting the music files.

The music list providing unit provides a music list of the arrangedmusic files. The music list provides information of music files withrespect to the arranged music files, and the information of the musicfiles may include information of the title, lyrics, a singer of themusic. The user may check the information of the title, lyrics, thesinger of the music on the music list, and may select required music ormay select after listening to the music.

FIG. 8 is a flowchart illustrating a music recommendation method withrespect to a message service according to another embodiment of thepresent invention.

Referring to FIG. 8, in operation 810, a music recommendation systemselects music files according to a theme of the message service andmusic, a mood of the music, a similarity between content of the messageservice and content of the music. Herein after, the selecting of themusic files will be described in detail by referring to FIG. 9.

FIG. 9 is a flowchart illustrating an example of operations of analyzingthemes of FIG. 8.

Referring to FIG. 9, in operation 910, a music recommendation systemselects target music files. Specifically, in operation 910, the musicrecommendation system selects either a music file stored in a userterminal or a music file which is downloadable via a music downloadservice on an Internet connection, as the target music files.

In operation 920, the music recommendation system classifies the targetmusic files and the message service according to a theme, and selects,from among the target music files, a plurality of music files whichcorresponds to the theme of the message according to a result of theclassification. Hereinafter, the classification of the target musicfiles will be described in detail by referring to FIG. 10.

FIG. 10 is a flowchart illustrating operations of the classifying of themusic files according to the theme of FIG. 9.

Referring to FIG. 10, in operation 1011, a music recommendation systemclassifies a title of music of target music files according to a theme.

In operation 1012, the music recommendation system classifies lyrics ofthe music of the target music files.

In operation 1020, the music recommendation system merges a result ofthe classification of the lyrics with a result of the classification ofthe title.

In operation 1030, the music recommendation system classifies the targetmusic files according to a theme, based on the merged results of theclassification of the lyrics and the title. A theme of the music filesmay be variously defined depending on categories such as sorrow,happiness, love, a breakup, yearning, spring, summer, autumn, winter,and a journey. When a specific music does not fall into the definedcategories, the specific music may be classified into the others.Hereinafter, the selecting of the target music files will be describedin detail by referring to FIG. 11.

FIG. 11 is a flowchart illustrating an example of operations ofselecting a music file according to the theme of FIG. 9.

Referring to FIG. 11, in operation 1110, a music recommendation systemclassifies a message service according to a theme. Similar to the themeof the target music files, the theme of the message service may bevariously defined depending on categories such as sorrow, happiness,love, a breakup, yearning, spring, summer, autumn, winter, and ajourney. When a specific music does not correspond to the definedcategories, the specific music may be classified into the others.

In operation 1120, the music recommendation system selects music filesappropriate for the theme of the message service based on the classifiedtheme of the music target music files. Specifically, in operation 1120,the music recommendation system may select a plurality of music filescorresponding to the theme of the classified message service, from acollection of the classified target music files.

In operation 930, the music recommendation system classifies theplurality of music files according to a mood, and filters out a musicfile whose mood is inappropriate for the theme of the music files.

In operation 940, the music recommendation system filters the pluralityof the music files according to a similarity between content of themessage service and content of the music files. Hereinafter, thefiltering of the plurality of the music files according to thesimilarity between the content of the message service and the content ofthe music files will be described in detail by referring to FIG. 12.

FIG. 12 is a flowchart illustrating an example of the filtering of theplurality of music files according to the similarity of FIG. 9.

Referring to FIG. 12, in operation 1210, a music recommendation systemindexes a title and lyrics of music files, stored in a database, andcontent of a message service. Specifically, in operation 1210, the musicrecommendation system extracts character strings of a text from themessage service inputted by the user, and indexes the message service byexpressing the character strings of the text as a vector. In this case,a morpheme n-gram and a word n-gram may be used for the characterstrings of the text, and features to be selected in operation 1310 maybe used for the character strings of the text. Feature values may beindexed by calculating a number of each features' occurring in themessage service or the lyrics using a frequency weight.

In operation 1220, the music recommendation system calculates asimilarity content of indexed music files and content of indexed messageservice. Specifically, in operation 1220, the music recommendationsystem calculates the similarity between the content of the music filesand the content of message service using a vector of the content of theindexed music files and a vector of the content of the indexed messageservice. In this case, a cosine similarity may be used for thesimilarity between the content of the music files and the content of themessage service.

In operation 1230, the music recommendation system compares thesimilarity with a threshold value. Specifically, the musicrecommendation system compares the similarity with the threshold valueto determine whether the similarity between the content of the musicfiles and the content of the message service is greater than or equal tothe threshold value, or less than the threshold value.

In operation 1240, the music recommendation system determines whetherthe similarity is greater than the threshold value. When the similarityis less than the threshold value, operation process returns to operation1210.

In operation 1250, the music recommendation system selects music fileswhose similarity is greater than the threshold value. Specifically, inoperation 1250, the music recommendation system may select the musicfiles whose similarity between the content of the music files and thecontent of the message service is equal to or greater than the thresholdvalue.

FIG. 13 is a flowchart illustrating an example of operations ofclassification of a theme of lyrics, a theme of a title, and a theme ofa message service of FIG. 11.

Referring to FIG. 13, in operation 1310, a music recommendation systemselects a feature via learning, from music files stored in a database ora collection of a message service. Specifically, in operation 1310, themusic recommendation system may select the feature to be used for themeclassification, from a title and lyrics of the music files stored in thedatabase or the message service.

In operation 1320, the music recommendation system indexes one of acategory of the music files or the message service using the selectedfeature.

In operation 1330, the music recommendation system pre-processes themusic files stored in a user terminal and the message service inputtedby a user.

In operation 1340, the music recommendation system indexes a music fileand a message service according to a result of the pre-processing.

In operation 1350, the music recommendation system allocates eachcategory to the indexed music files and the message service based on aresult of the category index.

Operations 1310 and 1320 are performed using a music file collectionstored in the database, the database being previously built, and themessage service. Also, operations 1310 and 1320 may be performed inadvance when building a system, not at a point of when a user uses thesystem, since operations 1310 and 1320 correspond to operation of thelearning. Operations 1330, 1340, and 1350 are performed during operationof classification of music and a message, and a target of operations1330, 1340, and 1350 is a music file in a user terminal or a messageservice to be transmitted by the user.

In operation 820, the music recommendation system recommends appropriatemusic files for the message service to the user based on the themescalculated in operation 810 and a similarity value between the contentsof the music files and the message service. Specifically, in operation820, the music recommendation system arranges the music files based onthemes calculated in operation 810 and the similarity value between thecontents of the music files and the message service to recommend thearranged music files to the user.

As an example, in operation 820, the music recommendation system mayrecommend to the user a music list whose selected music files arearranged in a descending order by using the similarity value.Specifically, in operation 820, the music recommendation system mayinclude the arranging of the selected music files, and the providing ofthe music list of the arranged selected music files. The music list mayinclude a title, lyrics, and a singer of music. The user may checkinformation of the title, the lyrics, and the singer of the music on themusic list, and select required music or select after listening to themusic.

The music recommendation method according to the above-describedembodiment of the present invention may be recorded in computer-readablemedia including program instructions to implement various operationsembodied by a computer. The media may also include, alone or incombination with the program instructions, data files, data structures,and the like. Examples of computer-readable media include magnetic mediasuch as hard disks, floppy disks, and magnetic tape; optical media suchas CD ROM disks and DVD; magneto-optical media such as optical disks;and hardware devices that are specially configured to store and performprogram instructions, such as read-only memory (ROM), random accessmemory (RAM), flash memory, and the like. The media may also be atransmission medium such as optical or metallic lines, wave guides, andthe like, including a carrier wave transmitting signals specifying theprogram instructions, data structures, and the like. Examples of programinstructions include both machine code, such as produced by a compiler,and files containing higher level code that may be executed by thecomputer using an interpreter. The described hardware devices may beconfigured to act as one or more software modules in order to performthe operations of the above-described embodiments of the presentinvention.

According to the present invention, there are provided a musicrecommendation method which can select a music file according to a themeof the music, a mood of the music, and a similarity between content of amessage service and content of the music, and automatically recommend toa user the selected music file, and a music recommendation system usingthe method.

Also, according to the present invention, there are provided a musicrecommendation method which can classify a title of music, lyrics of themusic, and a text of a message service according to a theme, compare theclassified theme, and select the music as a result of the comparison,and a music recommendation system using the method.

Also, according to the present invention, there are provided a musicrecommendation method which can recommend music, which is matched with atheme of a message service, by classifying music according to a theme,and also classifying the music according to a mood in a personalcommunication terminal, and a music recommendation system using themethod.

Also, according to the present invention, there are provided a musicrecommendation method which can accurately select music, which ismatched with a message service, by calculating a similarity betweencontent of lyrics and content of the message service, and a musicrecommendation system using the method.

Although a few exemplary embodiments of the present invention have beenshown and described, the present invention is not limited to thedescribed exemplary embodiments. Instead, it would be appreciated bythose skilled in the art that changes may be made to these exemplaryembodiments without departing from the principles and spirit of theinvention, the scope of which is defined by the claims and theirequivalents.

What is claimed is:
 1. A music recommendation method with respect to amessage inputted by a user, for transmitting via a message service in apersonal communication terminal, the method comprising: selecting musicfiles according to a theme of the message, a theme of a music, and amood of the music, determining whether the number of selected musicfiles is greater than a predetermined number, and, if the number ofselected music files is greater than the predetermined number, thenfurther selecting music files from the selected music files according toa similarity between content of the message and content of the music;and recommending the selected music files to the user.
 2. The method ofclaim 1, wherein the selecting of the music files further comprises:selecting target music files; and classifying the target music files andthe message according to a theme, selecting at least one music filewhich corresponds to the theme of the message according to a result ofthe classification, from among the target music files, and generating alist including the at least one music file.
 3. The method of claim 2,wherein the selecting of the music files further comprises: classifyingeach of music files of the list according to a mood, and eliminating atleast one music file, whose mood is inappropriate for the theme of themessage, from the list.
 4. The method of claim 2, wherein theclassifying of the target music files comprises: classifying lyrics ofthe music files according to the theme; classifying a title of the musicfiles according to the theme; classifying the message according to atheme; merging a result of the classification of the lyrics with aresult of the classification of the title; and the classifying thetarget music files according to the theme, is based on a result of themerged classification.
 5. The method of claim 4, wherein the classifyingof the lyrics, the title, or the message according to the themecomprises: selecting a feature to be used for the theme classificationfrom music files, stored in a database, or a collection of the message;indexing one category using the selected feature; pre-processing themusic files stored in a personal mobile terminal and a message inputtedby the user; indexing the music files and the message according to aresult of the pre-processing; and allocating each category to theindexed music files and the message based on a result of the indexing ofthe category.
 6. The method of claim 1, wherein the further selectingmusic files from the selected music files according to a similaritybetween content of the message and content of the music comprises:indexing the content of the message and the content of the music files;calculating a similarity between the indexed content of the message andthe indexed content of the music files; comparing the calculatedsimilarity with a threshold value; and selecting the music files whenthe calculated similarity is greater than the threshold value.
 7. Themethod of claim 1, wherein the recommending of the selected music filesto the user comprises: arranging the music files further selectedaccording to the similarity; and providing a list of the arranged musicfiles.
 8. A computer-readable storage medium storing a program forimplementing a music recommendation method with respect to a messageinputted by a user, for transmitting via a message service in a personalcommunication terminal, the method comprising: selecting music filesaccording to a theme of the message, a theme of a music, and a mood ofthe music, determining whether the number of selected music files isgreater than a predetermined number, and, if the number of selectedmusic files is greater than the predetermined number, then furtherselecting music files from the selected music files according to asimilarity between content of the message and content of the music; andrecommending the selected music files to the user.
 9. A musicrecommendation system with respect to a message inputted by a user, fortransmitting via a message service in a personal communication terminal,the system comprising: a music file selection unit to select music filesaccording to a theme of the message, a theme of a music, and a mood ofthe music, filtering unit to determine whether the number of selectedmusic files is greater than a predetermined number, and, if the numberof selected music files is greater than a predetermined number, then tofurther select music files from the previously selected music filesaccording to a similarity between content of the message, and content ofthe music; and a recommendation unit to recommend the selected musicfiles to the user.
 10. The system of claim 9, wherein the music fileselection unit comprises: a selection unit to select target music files,classify the target music files and the message according to a theme,select at least one music file which corresponds to the theme of themessage according to a result of the theme classification, from amongthe target music files, and generate a list including the at least onemusic file.
 11. The system of claim 10, wherein the music file selectionunit further comprises: a first filtering unit to classify each of musicfiles of the list according to a mood, and to eliminate at least onemusic file from the list based on the mood.
 12. The system of claim 10,wherein the music file selection unit further comprises: a lyrics themeclassification unit to classify lyrics of the music files according to atheme; a title theme classification unit to classify a title of themusic files according to a theme; a message theme classification unit toclassify the message according to a theme; a classification resultmerging unit to merge a result of the classifications of the lyrics witha result of the classifying of the title; and a music selection unit toselect the plurality of the music files based on a music collectionclassified according to the theme and the message classified accordingto the theme.
 13. The system of claim 12, wherein each of the lyricstheme classification unit, the title theme classification unit, and themessage theme classification unit comprises: a feature selection unit toselect one of a feature of the title, the lyrics, or the message, whichis used for the theme classification from a database; a category indexunit to index one of a category of the title, the lyrics, or the messageusing the feature; a pre-processing unit to pre-process one of thetitle, the lyrics, or the message stored in the user personalcommunication terminal; an index unit to index the music files and themessage according to a result of the pre-processing; and a categoryallocation unit to allocate each category to the indexed music files andthe message based on a result of the indexing of the category.
 14. Thesystem of claim 9, wherein the filtering unit comprises: a message indexunit to index a content of a message inputted by the user; a lyricsindex unit to index a content of a title and lyrics of the previouslyselected music files; a similarity calculation unit to calculate asimilarity between (1) the indexed content of the title and lyrics, and(2) the indexed content of the message; a comparison unit to compare thecalculated similarity with a threshold value; and a selection unit toselect the music files when the calculated similarity is greater thanthe threshold value.
 15. The system of claim 9, wherein therecommendation unit comprises: a music arrangement unit to arrange themusic files further selected based on the similarity; and a music listproviding unit to provide a list of the arranged music files.